SPOKE CONNECTOR

[Suhail2297]

Hello everyone,

How can i achieve this?

"Configure the Spoke connector for real-time discovery of CCTV cameras" for Cisco Meraki Dashboard Integration

[Abbas_5 · Accepted solution]

Hello @Suhail2297,

To configure a Spoke connector for real-time discovery of CCTV cameras in ServiceNow, you'll need to create a custom Spoke that leverages the capabilities of the ServiceNow AI Platform and Integration Hub. This Spoke will handle the specific data collection and integration steps needed for CCTV cameras. 

1. Define the Spoke's Purpose and Data Requirements:

• Goal:

  Real-time discovery of CCTV cameras, capturing relevant data such as IP address, model, location, and status.
• Data Requirements:

  • IP Address
  • Manufacturer and Model
  • Location (e.g., building, floor)
  • Status (e.g., online, offline, active, inactive)
  • Optional: Camera resolution, storage capacity, etc.

2. Develop the Spoke Connector:

• Choose a Spoke Type:

  Select a suitable Spoke type (e.g., REST, SOAP, or custom) based on the communication method used by your CCTV camera systems.
• Authentication:

  Implement the necessary authentication mechanisms to connect to the CCTV camera system. This might involve usernames, passwords, or API keys.
• Discovery Logic:

  Write code to:

  • Discover the list of CCTV cameras.
  • Extract relevant data from each camera.
  • Format the data in a way that can be easily mapped to ServiceNow CI classes.
• CI Mapping:

  Map the discovered data to appropriate CI classes in ServiceNow. You might create a new CI class for CCTV cameras, or modify an existing one.
• Data Transformation:

  If needed, transform the data to match ServiceNow's data formats.
• Data Upload to ServiceNow:

  Upload the discovered data to the CMDB. Consider using a bulk import or a flow for efficient data ingestion. 

3. Integrate with ServiceNow:

• Spoke Configuration:

  Configure the Spoke within the Integration Hub.
• Scheduling:

  Set up a schedule for the Spoke to run and discover CCTV cameras periodically.
• Flows:

  Create Flows to automate tasks related to discovery, data processing, and CI creation.
• Automated Processes:

  Integrate the Spoke with existing workflows for incident management or other relevant processes. 

4. Testing and Validation:

• Test the Spoke:

  Test the Spoke's ability to discover CCTV cameras and upload data to ServiceNow.
• Verify Data Accuracy:

  Ensure that the discovered data is accurate and properly mapped to CI classes.
• Monitor Discovery:

  Monitor the discovery process to identify any issues or errors.
• Tune Discovery:

  Adjust the Spoke's configuration and scheduling as needed to optimize performance and accuracy. 

Example Spoke Scenario (REST API Discovery): 

1. Spoke Type: REST
2. Authentication: API Key
3. Discovery Logic:
   • Send a REST API request to the CCTV system to list all cameras.
   • Parse the JSON response to extract camera information.
4. CI Mapping: Map the data to a custom cmdb_ci_cctv CI class.
5. Data Upload: Upload the data to ServiceNow using a bulk import or a flow. 

Key Considerations:

• Security: Secure the Spoke connector to prevent unauthorized access.
• Performance: Ensure that the Spoke does not overload the CCTV system or ServiceNow.
• Error Handling: Implement robust error handling to manage potential issues.
• Documentation: Document the Spoke configuration and workflows.

By following these steps, you can successfully configure a Spoke connector for real-time discovery of CCTV cameras in ServiceNow, providing valuable data for your CMDB and various IT processes. 

If this is helpful, please hit the thumbs up button and accept the correct solution by referring to this solution in future it will be helpful to them.

Thanks & Regards,

Abbas Shaik